Radar AI Edition 2024: Welcome to Radar!

WebinarJuly 2024

Summary

Generative AI has evolved into a transformative force, motivating businesses to explore new opportunities and reshaping the skills requirements across organizations. Jonathan Cornelison, CEO of Datacamp, highlights three critical developments in AI: the widespread use of AI in businesses, the increasing power and availability of AI models, and the evolving skills needs crucial for effective AI usage. The conversation explores the grassroots and production use of AI, emphasizing the need for skilled talent to manage the associated challenges. Cornelison also discusses the quick advancements in AI models and the necessity for organizations to upskill their workforce in response to this significant shift. Moreover, Datacamp is adapting to these changes by expanding its curriculum to include AI skills and integrating AI features into its platform, improving learning experiences. The session lays the foundation for a deeper understanding of these themes over the two-day Radar event, featuring insights from industry leaders and organizations.

Key Takeaways:

AI's use in businesses is leading to significant productivity improvements but brings challenges such as data privacy and ethical use.
AI models are becoming more powerful and available, with open-source models gaining popularity.
The skills requirements are changing, requiring organizations to upskill their workforce for effective AI usage.
Datacamp is improving its curriculum and platform to support AI learning and application.
The Radar event will further explore these themes with insights from leading AI organizations.

Deep Dives

AI Adoption in Business

The adoption of AI in busine ...
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sses is accelerating, driven by tools like ChatGPT and Google Gen M&I. These technologies are being integrated at both grassroots and production levels within organizations. As stated by Jonathan Cornelison, "61% of white-collar workers use Gen AI in the workplace, saving an average of five hours per week." However, this integration comes with challenges such as the risk of hallucination, ethical concerns, and data privacy issues. Organizations must address these talent-based challenges to fully leverage AI's potential. While experimentation with AI is widespread, deploying AI into production remains a challenge, with only 9% of organizations achieving this. Legal concerns, infrastructure, and skill gaps are key barriers to progress.

Generative AI Enterprise Use Cases

AI models are evolving quickly, becoming stronger, faster, and cheaper. Proprietary models from industry giants like Google and OpenAI are pushing the limits of AI capabilities. Additionally, open-source models like Metas Llama3 and Databricks DBRX are providing competitive alternatives for various use cases. These advancements highlight the increasing strength of the open-source AI ecosystem. As models improve, they offer organizations unprecedented opportunities to use AI for diverse applications, from improving productivity to developing innovative solutions. The growing power and availability of AI models show the need for organizations to keep up with technological advancements and adjust their strategies accordingly.

Workforce Upskilling for AI

The rise of AI has reshaped the skills requirements, emphasizing the importance of upskilling and reskilling the workforce. Organizations must equip their employees with the skills necessary to manage AI's ethical, privacy, and quality challenges. As per Cornelison, "62% of leaders believe their organization has an AI literacy gap." Datacamp is responding to this need by expanding its curriculum to cover a wide range of AI skills, from technical courses for data scientists to ethical AI training for all employees. This comprehensive approach ensures that organizations can develop a workforce capable of using AI responsibly and effectively, bridging the current skills gap.

DataCamp AI Courses

Datacamp is a leader in AI education, adjusting its offerings to meet the changing needs of learners and organizations. The company has introduced over 80 projects, courses, and code-alongs focused on AI skills, curated by top instructors. Datacamp's platform now features AI-driven tools such as error explanations and AI assistants, improving the learning experience. The transformation of Datacamp Workspace into Datalab shows the company's commitment to integrating AI into its platform, providing users with a collaborative environment for data work. This evolution supports learners in acquiring the skills necessary to succeed in an AI-driven world, ensuring they remain competitive and competent.